Senior Data Scientist; Product, Crypto

Requirements

• You have 5+ years of experience in data science, analytics, or a related field
• You have strong proficiency in SQL and Python for data analysis and modeling
• You have experience designing experiments and interpreting results to guide product decisions
• You have domain knowledge in crypto, including onchain data and DeFi ecosystems
• You communicate clearly with both technical and non-technical partners

• We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers
• Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards
• The Crypto team’s mission is to build the next global financial ecosystem using blockchain technology, enabling scalable and accessible onchain financial products. This team plays a central role in advancing Robinhood’s focus on crypto and international expansion by developing products that expand access to decentralized finance
• As a Senior Data Scientist, you will lead analytical efforts supporting the launch and growth of Robinhood’s crypto platform, helping bring onchain and digital financial solutions to a global audience
• You’ll be at the forefront of shaping Robinhood’s crypto strategy using data, partnering closely with product, engineering, and finance to launch and optimize features across trading, international expansion, and wallet experiences
• Your work will guide product decisions through well-designed experiments and robust analysis, helping millions of customers engage more deeply with the crypto ecosystem
• Partner with product managers to identify opportunities across Robinhood's crypto platform, including trading, perpetuals, and tokenized assets
• Design and evaluate experiments to inform product decisions, using clear success metrics tied to business outcomes
• Analyze platform and market data to build datasets that power product insight
• Develop models to assess product performance, user behavior, and market dynamics
• Communicate findings to stakeholders including engineering, finance, and design teams to support product development